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Investigation of material models on deep drawing and ironing processes

Yıl 2022, Cilt: 11 Sayı: 2, 387 - 392, 15.04.2022
https://doi.org/10.28948/ngumuh.1034351

Öz

Within the scope of this study, the effects of yield and hardening criteria used in forming simulations on part geometric dimensions were investigated. As material 0.8 mm thick DC04 material is used. In the study, the results were compared using the Hill-48 and Barlat-91 yield criteria and experimental flow curve, Hockett-Sherby, Ludwig and Hollomon flow curve models. The studies were carried out in Simufact Sheet Metal Form software. Although all the models studied because of dimensional evaluations estimated within tolerance values, the model in which the experimental data were used with Hill-48 gave the closest results to the nominal dimensions.

Kaynakça

  • V. L. Hattalli and S. R. Srivatsa, Sheet metal forming processes–recent technological advances, Materials Today: Proceedings, 5, 2564-2574, 2018. https://doi.org/10.1016/j.matpr.2017.11.040
  • Y. Jia, Y. Qiao, H. Pan, E. Chu, and Y. Bai, A Comprehensive plasticity and fracture model for metal sheets under multi-axial stress and non-linear strain path, SAE International Journal of Engines, 10, 266-273, 2017. https://doi:10.4271/2017-01-0315
  • H. Zeng, Z. Huang, T. Wang, H. Sun, and L. Wang, Optimal design and forming analysis of the stamping process for front wall of automobile considering springback compensation technology, SAE Technical Paper, 0148-7191, 2021. https://doi.org/10.4271/2021-01-0269
  • Z. Wang, T. Hakoyama, Y. Endo, and K. Osakada, Application of flow model in metal cutting to cold forging of tubular products, CIRP Annals, 68, 273-276, 2019. https://doi.org/10.1016/j.cirp.2019.04.033
  • K. Zhao, L. Wang, Y. Chang, and J. Yan, Identification of post-necking stress–strain curve for sheet metals by inverse method, Mechanics of Materials, 92, 107-118, 2016. https://doi.org/10.1016/j.mechmat.2015.09.004
  • I. Mirandola, G. A. Berti, R. Caracciolo, S. Lee, N. Kim, and L. Quagliato, Machine learning-based models for the estimation of the energy consumption in metal forming processes, Metals, 11, 833, 2021. https://doi.org/10.3390/met11050833
  • Q.-F. Zhang, Z.-Y. Cai, Y. Zhang, and M.-Z. Li, Springback compensation method for doubly curved plate in multi-point forming, Materials & Design, 47, 377-385, 2013. https://doi.org/10.1016/j.matdes.2012. 12.005
  • J. Abu Qudeiri, A. Ziout, M. Alsayyed, A. Alzarooni, F. Safieh, A. Al Hatti, et al., Simulation study of deep drawing process, in Materials Science Forum, 2020, 139-147. https://doi.org/10.4028/www.scientific.net/ MSF.977.139
  • S. Tatipala, J. Pilthammar, M. Sigvant, J. Wall, and C. M. Johansson, Introductory study of sheet metal forming simulations to evaluate process robustness, in IOP Conference Series: Materials Science and Engineering, 2018, 012111. https://doi:10.1088/1757-899X/418/1/012111
  • A. Zabala, E. S. de Argandoña, D. Cañizares, I. Llavori, N. Otegi, and J. Mendiguren, Numerical study of advanced friction modelling for sheet metal forming: Influence of the die local roughness, Tribology International, 165, 107259, 2022. https://doi.org/10.1016/j.triboint.2021.107259
  • M. Ramezani and Z. Ripin, Introduction to sheet metal forming processes, Rubber-Pad Forming Processes—Technology and Applications, Elsevier, Amsterdam, 1-22, 2012.
  • Y. Qin, W. A. W. Nawang, and J. Zhao, Forming of micro sheet-metal components, in Micromanufacturing Engineering and Technology, ed, 2015, 299-322. https://doi.org/10.1016/B978-0-323-31149-6.00013-X
  • O. Çavuşoğlu, S. Toros, H. Gürün, and A. Güral, Warm deformation and fracture behaviour of DP1000 advanced high strength steel, Ironmaking & Steelmaking, 45, 618-625, 2018. https://doi.org/10. 1080/03019233.2017.1309168
  • J. Lian, F. Shen, X. Jia, D.-C. Ahn, D.-C. Chae, S. Münstermann, et al., An evolving non-associated Hill48 plasticity model accounting for anisotropic hardening and r-value evolution and its application to forming limit prediction, International Journal of Solids and Structures, 151, 20-44, 2018. https://doi.org/10.1016/j.ijsolstr.2017.04.007
  • D. Banabic, Sheet metal forming processes: constitutive modelling and numerical simulation: Springer Science & Business Media, 2010.
  • B. Şener, T. A. Akşen, and M. Fırat, On the effect of through-thickness integration for the blank thickness and ear formation in cup drawing FE analysis, European Mechanical Science, 5, 51-55, 2021. https://doi.org/10.26701/ems.781175

Derin çekme ve ütüleme proseslerinde malzeme modellerinin incelenmesi

Yıl 2022, Cilt: 11 Sayı: 2, 387 - 392, 15.04.2022
https://doi.org/10.28948/ngumuh.1034351

Öz

Bu çalışma kapsamında, şekillendirme simülasyonlarında kullanılan akma ve pekleşme kriterlerinin parça geometrik boyutlarına etkisi incelenmiştir. Malzeme olarak 0.8 mm kalınlığındaki DC04 malzemesi kullanılmıştır. Çalışmada Hill-48 ve Barlat-91 akma kriterleri ile deneysel akma eğrisi, Hockett-Sherby, Ludwig ve Hollomon akma eğrisi modelleri kullanılarak sonuçlar karşılaştırılmıştır. Çalışmalar Simufact Sheet Metal Form yazılımda gerçekleştirilmiştir. Boyutsal değerlendirmeler neticesinde çalışılan bütün modeller her ne kadar tolerans değerleri içerisinde tahmin etmiş olsa da deneysel verilerinin Hill-48 ile kullanıldığı model nominal boyutlara en yakın sonuçları vermiştir.

Kaynakça

  • V. L. Hattalli and S. R. Srivatsa, Sheet metal forming processes–recent technological advances, Materials Today: Proceedings, 5, 2564-2574, 2018. https://doi.org/10.1016/j.matpr.2017.11.040
  • Y. Jia, Y. Qiao, H. Pan, E. Chu, and Y. Bai, A Comprehensive plasticity and fracture model for metal sheets under multi-axial stress and non-linear strain path, SAE International Journal of Engines, 10, 266-273, 2017. https://doi:10.4271/2017-01-0315
  • H. Zeng, Z. Huang, T. Wang, H. Sun, and L. Wang, Optimal design and forming analysis of the stamping process for front wall of automobile considering springback compensation technology, SAE Technical Paper, 0148-7191, 2021. https://doi.org/10.4271/2021-01-0269
  • Z. Wang, T. Hakoyama, Y. Endo, and K. Osakada, Application of flow model in metal cutting to cold forging of tubular products, CIRP Annals, 68, 273-276, 2019. https://doi.org/10.1016/j.cirp.2019.04.033
  • K. Zhao, L. Wang, Y. Chang, and J. Yan, Identification of post-necking stress–strain curve for sheet metals by inverse method, Mechanics of Materials, 92, 107-118, 2016. https://doi.org/10.1016/j.mechmat.2015.09.004
  • I. Mirandola, G. A. Berti, R. Caracciolo, S. Lee, N. Kim, and L. Quagliato, Machine learning-based models for the estimation of the energy consumption in metal forming processes, Metals, 11, 833, 2021. https://doi.org/10.3390/met11050833
  • Q.-F. Zhang, Z.-Y. Cai, Y. Zhang, and M.-Z. Li, Springback compensation method for doubly curved plate in multi-point forming, Materials & Design, 47, 377-385, 2013. https://doi.org/10.1016/j.matdes.2012. 12.005
  • J. Abu Qudeiri, A. Ziout, M. Alsayyed, A. Alzarooni, F. Safieh, A. Al Hatti, et al., Simulation study of deep drawing process, in Materials Science Forum, 2020, 139-147. https://doi.org/10.4028/www.scientific.net/ MSF.977.139
  • S. Tatipala, J. Pilthammar, M. Sigvant, J. Wall, and C. M. Johansson, Introductory study of sheet metal forming simulations to evaluate process robustness, in IOP Conference Series: Materials Science and Engineering, 2018, 012111. https://doi:10.1088/1757-899X/418/1/012111
  • A. Zabala, E. S. de Argandoña, D. Cañizares, I. Llavori, N. Otegi, and J. Mendiguren, Numerical study of advanced friction modelling for sheet metal forming: Influence of the die local roughness, Tribology International, 165, 107259, 2022. https://doi.org/10.1016/j.triboint.2021.107259
  • M. Ramezani and Z. Ripin, Introduction to sheet metal forming processes, Rubber-Pad Forming Processes—Technology and Applications, Elsevier, Amsterdam, 1-22, 2012.
  • Y. Qin, W. A. W. Nawang, and J. Zhao, Forming of micro sheet-metal components, in Micromanufacturing Engineering and Technology, ed, 2015, 299-322. https://doi.org/10.1016/B978-0-323-31149-6.00013-X
  • O. Çavuşoğlu, S. Toros, H. Gürün, and A. Güral, Warm deformation and fracture behaviour of DP1000 advanced high strength steel, Ironmaking & Steelmaking, 45, 618-625, 2018. https://doi.org/10. 1080/03019233.2017.1309168
  • J. Lian, F. Shen, X. Jia, D.-C. Ahn, D.-C. Chae, S. Münstermann, et al., An evolving non-associated Hill48 plasticity model accounting for anisotropic hardening and r-value evolution and its application to forming limit prediction, International Journal of Solids and Structures, 151, 20-44, 2018. https://doi.org/10.1016/j.ijsolstr.2017.04.007
  • D. Banabic, Sheet metal forming processes: constitutive modelling and numerical simulation: Springer Science & Business Media, 2010.
  • B. Şener, T. A. Akşen, and M. Fırat, On the effect of through-thickness integration for the blank thickness and ear formation in cup drawing FE analysis, European Mechanical Science, 5, 51-55, 2021. https://doi.org/10.26701/ems.781175

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliği
Bölüm Makine Mühendisliği
Yazarlar

Cihangir KAPLAN 0000-0002-6972-7959

Cem GÜLEÇ 0000-0002-5612-6572

Mesut ARIKOĞLU 0000-0002-7198-1905

Serkan TOROS 0000-0003-0438-2862

Habip Gökay KORKMAZ 0000-0003-2670-7912

Yayımlanma Tarihi 15 Nisan 2022
Gönderilme Tarihi 14 Aralık 2021
Kabul Tarihi 7 Mart 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 11 Sayı: 2

Kaynak Göster

APA KAPLAN, C., GÜLEÇ, C., ARIKOĞLU, M., TOROS, S., vd. (2022). Investigation of material models on deep drawing and ironing processes. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 11(2), 387-392. https://doi.org/10.28948/ngumuh.1034351
AMA KAPLAN C, GÜLEÇ C, ARIKOĞLU M, TOROS S, KORKMAZ HG. Investigation of material models on deep drawing and ironing processes. NÖHÜ Müh. Bilim. Derg. Nisan 2022;11(2):387-392. doi:10.28948/ngumuh.1034351
Chicago KAPLAN, Cihangir, Cem GÜLEÇ, Mesut ARIKOĞLU, Serkan TOROS, ve Habip Gökay KORKMAZ. “Investigation of Material Models on Deep Drawing and Ironing Processes”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 11, sy. 2 (Nisan 2022): 387-92. https://doi.org/10.28948/ngumuh.1034351.
EndNote KAPLAN C, GÜLEÇ C, ARIKOĞLU M, TOROS S, KORKMAZ HG (01 Nisan 2022) Investigation of material models on deep drawing and ironing processes. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 11 2 387–392.
IEEE C. KAPLAN, C. GÜLEÇ, M. ARIKOĞLU, S. TOROS, ve H. G. KORKMAZ, “Investigation of material models on deep drawing and ironing processes”, NÖHÜ Müh. Bilim. Derg., c. 11, sy. 2, ss. 387–392, 2022, doi: 10.28948/ngumuh.1034351.
ISNAD KAPLAN, Cihangir vd. “Investigation of Material Models on Deep Drawing and Ironing Processes”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 11/2 (Nisan 2022), 387-392. https://doi.org/10.28948/ngumuh.1034351.
JAMA KAPLAN C, GÜLEÇ C, ARIKOĞLU M, TOROS S, KORKMAZ HG. Investigation of material models on deep drawing and ironing processes. NÖHÜ Müh. Bilim. Derg. 2022;11:387–392.
MLA KAPLAN, Cihangir vd. “Investigation of Material Models on Deep Drawing and Ironing Processes”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, c. 11, sy. 2, 2022, ss. 387-92, doi:10.28948/ngumuh.1034351.
Vancouver KAPLAN C, GÜLEÇ C, ARIKOĞLU M, TOROS S, KORKMAZ HG. Investigation of material models on deep drawing and ironing processes. NÖHÜ Müh. Bilim. Derg. 2022;11(2):387-92.

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